Prevalence and factors associated with cognitive frailty in heart failure: a systematic review and meta-analysis protocol

Abstract

Introduction

Heart failure (HF) is a global health issue affecting millions of people worldwide. Cognitive frailty, a syndrome characterised by physical frailty and cognitive impairment without dementia, is increasingly recognised in this population. Cognitive frailty is associated with worse outcomes, including increased hospitalisation, disability and mortality. This systematic review and meta-analysis aimed to investigate the incidence, prevalence and predictors of cognitive frailty in HF patients.

Methods

A systematic search will be conducted in MEDLINE/PubMed, EMBASE/Ovid, Web of Science and Google Scholar from inception to the latest search date. Eligible studies will report original data on adult patients (age ≥18 years) with HF, focusing on the incidence, prevalence and predictors of cognitive frailty. Two investigators will independently extract data and assess study quality using the Newcastle-Ottawa Scale and mixed-methods appraisal tool. Meta-analyses and meta-regression will be performed to estimate the pooled prevalence of cognitive frailty in HF patients and to identify predictors associated with increased risk, respectively. Subgroup analyses will be conducted to explore potential sources of heterogeneity.

Ethics and dissemination

This systematic review does not require ethical approval and informed consent, as it does not use identifiable patient data. The results of this study will be submitted for publication in a peer-reviewed medical journal. This comprehensive meta-analysis of the literature on cognitive frailty among HF patients will inform tailored interventions and management strategies, ultimately improving patients’ quality of life and outcomes.

Correspondence to Dr Olayiwola Akeem Bolaji; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• A comprehensive search strategy across multiple databases and the use of standardised quality assessment tools like the Newcastle-Ottawa Scale ensure robust and consistent data evaluation.

• The involvement of two independent investigators for data extraction and quality assessment effectively minimises bias, enhancing the study’s credibility.

• Advanced statistical methods, including meta-analysis and meta-regression, provide precise estimates of cognitive frailty prevalence and allow for the identification of predictors and sources of heterogeneity.

• The study may be subject to publication bias and variability in methodologies, diagnostic criteria and assessment tools across included studies, potentially leading to an overestimation of effect sizes and introducing heterogeneity.

• Limiting the review to English-language articles and relying solely on data from included studies could affect the generalisability of findings and leave potential residual confounding factors unaddressed.

Introduction

Heart failure (HF) is a complex clinical syndrome that arises from structural or functional cardiac disorders, leading to impaired ventricular filling or ejection of blood.¹ Affecting more than 26 million people globally, HF is associated with substantial morbidity, mortality and healthcare costs, presenting a significant public health concern.^{2 3} The prevalence of HF is projected to rise due to factors such as an ageing population and improved survival rates of patients with cardiovascular diseases.⁴

Cognitive frailty is a clinical syndrome characterised by the presence of both physical frailty and cognitive impairment without concurrent dementia.⁵ Physical frailty is a state of increased vulnerability to stressors resulting from a decline in reserve and function across multiple physiological systems.⁶ Cognitive impairment involves a decline in cognitive abilities, such as memory, attention and executive function, that is more significant than age-related cognitive decline but does not meet the criteria for dementia.⁷

HF patients are at an increased risk of developing cognitive frailty due to several factors. Reduced cerebral blood flow, secondary to impaired cardiac function, may lead to cerebral hypoperfusion, contributing to cognitive decline.^{8 9} Chronic systemic inflammation, commonly observed in HF patients, can accelerate neuroinflammation and exacerbate cognitive impairment.^{10 11} Additionally, comorbidities such as hypertension, diabetes and atrial fibrillation, often present in HF patients, further increase the risk of cognitive frailty.^{12 13}

Cognitive frailty is associated with worse outcomes, including increased hospitalisation, disability and mortality, and has significant implications for patient’s quality of life and healthcare resource utilisation.^{14 15} Therefore, understanding the incidence, prevalence and predictors of cognitive frailty in HF patients is critical for early identification and intervention. This systematic review and meta-analysis aim to investigate the incidence, prevalence and predictors of cognitive frailty in HF patients.

Methods

Study design

A systematic review and meta-analysis will be conducted in accordance with the Cochrane Handbook for Systematic Reviews of Interventions⁶ and by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist.⁷ The protocol for this systematic review has been registered with the Open Science Framework (OSF) and assigned a digital object identifier (DOI): https://doi.org/10.17605/OSF.IO/326GF.

Review questions

• What is the incidence and prevalence of cognitive frailty among patients with heart failure?

• What factors are associated with an increased risk of cognitive frailty in patients with heart failure?

Search strategy

Two independent investigators will systematically search the online literature in the following databases: MEDLINE/PubMed, EMBASE/Ovid, Web of Science, Cochrane Library and Google Scholar from inception to the latest search date. A combination of search terms reflecting the review questions will be employed, including ‘heart failure’, ‘cognitive frailty’, ‘cognitive impairment’, ‘mild cognitive impairment’, ‘frailty’, ‘incidence’, ‘prevalence’ and ‘predictors’. The precise search strategy, including Medical Subject Headings (MeSH) terms and keywords, is presented in the online supplemental file 1 for MEDLINE/PubMed. This strategy will be adapted for each database in consultation with an experienced librarian specialising in the biomedical literature review. Reference lists of eligible studies and relevant reviews will also be hand-searched to identify additional studies.

Study eligibility

Inclusion criteria

• Full-text articles available in the English language.

• Original data on adult patients (age ≥18 years) with heart failure.

• Studies reporting the incidence, prevalence or predictors of cognitive frailty in heart failure patients using validated cognitive and frailty assessment tools.

Exclusion criteria

• Review articles, editorials, commentaries or reanalysis of previously published datasets without original data.

• Studies not focused on heart failure patients or cognitive frailty.

• Full text not available or not in English.

• Case reports, case series or single-arm studies with inherent methodological limitations.

Data extraction

Two independent investigators will be responsible for extracting data from the selected studies to maintain robustness and reliability in our systematic review and meta-analysis. This method of extraction is aimed at ensuring inter-rater reliability and reducing biases. In cases where discrepancies arise between the two primary investigators, a third investigator will mediate the disagreements, ensuring the extraction process remains consistent and accurate. We will contact the study’s senior author for clarification if there is ambiguity or a need for additional information regarding any extracted data.

The data to be extracted will encompass several parameters, including:

• Type of study: To provide an understanding of the study design and methodology, ensuring appropriate categorisation and analysis.

• Country of origin: To assess potential geographical patterns and regional differences in the incidence or prevalence of cognitive frailty.

• Number of patients: This indicates the sample size and, subsequently, the power of the study.

• Patients’ demographics: Details such as age, gender and ethnicity can be pivotal in analysing disparities or patterns in cognitive frailty across different populations.

• HF characteristics: It is crucial to understand the varying characteristics of HF among the studied populations, as this can influence cognitive frailty.

• Cognitive and frailty assessment methods: This will allow for understanding the methods and tools employed in the studies and the possibility of comparing or contrasting results.

• Incidence and prevalence of cognitive frailty: Direct metrics to understand the spread and occurrence of cognitive frailty in the studied groups.

• Predictors of cognitive frailty: To gain insights into possible causative or correlative factors.

• Pharmacological treatment details: We will extract data regarding the number/percentage of patients on each of the four pharmacological pillars of HF treatment. This data is essential as it might shed light on the correlation between HF treatment types and the potential prediction of cognitive frailty.

Quality assessment

The methodological quality of included studies will be assessed using the Newcastle-Ottawa Scale⁸ for cohort and case-control studies and the Cochrane Collaboration’s Risk of Bias tool⁶ for randomised controlled trials. Two independent investigators will perform quality assessments, with disagreements resolved through discussion or consultation with a third investigator. Quality scores will be reflected in the data synthesis results, but no study will be excluded based on quality assessment.

Meta-analysis

A meta-analysis will estimate the pooled incidence and prevalence of cognitive frailty in HF patients and identify predictors associated with increased risk. Random-effects or fixed-effects models will be employed based on the heterogeneity of the data, which will be assessed using the I2 statistic and Cochran’s Q test. Heterogeneity will be interpreted as low (I2<30%), moderate (30%≤I2<60%) or high (I2≥60%). Subgroup analyses and meta-regression will be conducted to explore potential sources of heterogeneity and evaluate the robustness of the findings.

Subgroup analysis

We will implement rigorous subgroup analyses to ensure a comprehensive and nuanced understanding of the relationship between HF and cognitive frailty. This methodological approach addresses potential variations attributable to study-specific methodologies and patient characteristics. Subgroup analyses will be stratified based on the following parameters:

• Diagnostic criteria for cognitive frailty: Different studies might use diverse diagnostic tools and criteria. By examining these separately, we intend to discern any inconsistencies or alignments that different diagnostic approaches may yield.

• HF aetiology: Given that HF can arise from numerous causes, discerning the relationship between specific aetiologies and cognitive frailty is imperative for a more granular understanding.

• HF severity: To ensure clarity and in-depth analysis, HF severity will be evaluated based on various metrics, including the following:

  • Left ventricular ejection fraction (LVEF): This metric gauges the proportion of blood pumped out by the left ventricle during each contraction.

  • Number of hospital admissions: Reflects the frequency of disease exacerbations and their subsequent management.

  • New York Heart Association (NYHA) functional class: By classifying HF severity based on the NYHA’s standards, we can grasp the influence of disease stages on cognitive frailty.

  • Quality of life: Various tools and questionnaires measure the perceived quality of life in HF patients, offering insights into the indirect ramifications of the disease on cognitive health.

  • Other indicators: Additional markers such as biomarker levels (like NT-proBNP or troponin), comorbid conditions, cardiac medication usage and patient-reported symptoms will also be included in the subgroup analysis as they are potential indicators that could reflect the severity of HF.

• Study design: Segregating based on study designs can aid in identifying methodological nuances and specific insights that might emerge from distinctive research methodologies.

Statistical tools

Statistical analyses will be conducted using STATA (V.17; StataCorp), R software and Comprehensive Meta-Analysis (CMA) software. Results will be considered statistically significant when the pooled estimates and 95% CIs do not include the null value or the p value is <0.05. Forest plots will be used to visualise the meta-analysis results, including the pooled incidence, prevalence and predictors of cognitive frailty. If more than 10 studies are available, a funnel plot will be constructed to assess potential publication bias, with Egger’s and Begg’s tests being employed to quantify the degree of bias.

Sensitivity analysis

A sensitivity analysis will be performed to assess the robustness of the meta-analysis results. This will involve sequentially removing one study at a time and rerunning the analysis to evaluate whether the results are significantly affected by excluding any individual study. If necessary, additional sensitivity analyses may be conducted based on study quality, sample size or other factors that may influence the results.

Patient and public involvement

No patients will be directly involved in this study. However, patient perspectives on cognitive frailty and its impact on their lives may be considered while interpreting the findings and developing recommendations for clinical practice and future research.

Discussion

Cognitive frailty in HF patients is an emerging issue with significant implications for patient care and outcomes. As the global population ages and the prevalence of heart failure increases, understanding the interplay between cognitive frailty and HF becomes increasingly important. This systematic review and meta-analysis aim to provide a comprehensive overview of the incidence, prevalence and predictors of cognitive frailty in HF patients, which will have far-reaching implications for clinical practice and research.

By identifying the risk factors and understanding the magnitude of cognitive frailty in this population, healthcare providers can develop tailored interventions and management strategies to improve patient’s quality of life and outcomes. Early detection and treatment of cognitive frailty may lead to better patient adherence to medication regimens, enhanced self-care and improved management of comorbidities, ultimately reducing hospitalisations and healthcare costs.

Furthermore, identifying modifiable predictors of cognitive frailty in HF patients may inform the development of targeted interventions to prevent or delay the onset of cognitive decline. Such interventions may include optimising the medical management of HF, addressing comorbidities and implementing lifestyle interventions such as physical activity, cognitive training, and dietary modifications.

This systematic review and meta-analysis will also contribute to the existing body of literature by synthesising data from various study designs, populations and settings, providing a comprehensive understanding of cognitive frailty in the context of HF. Additionally, the findings of this review help identify gaps in the current knowledge and guide future research in this area. For example, further studies may explore the impact of cognitive frailty on patient-reported outcomes, caregiver burden and healthcare resource utilisation in HF patients.

Ethics and dissemination

This systematic review does not require ethical approval and informed consent, as it does not use identifiable patient data. The results of this study will be submitted for publication in a peer-reviewed medical journal, ensuring that the findings are disseminated to the broader scientific community and healthcare professionals. The results will also be presented at relevant conferences, contributing to the ongoing dialogue on cognitive frailty and heart failure. Ultimately, this work aims to advance our understanding of the complex interplay between cognitive frailty and HF, informing clinical practice and improving patient care and outcomes.

Ethics statements

Patient consent for publication

Not applicable.

Footnote

Twitter @bolaji_oa

Contributors OAB originated the idea for this systematic review and meta-analysis protocol. He delineated the primary research questions, objectives and hypotheses to guide the study. A crucial contributor in drafting the protocol manuscript, he oversaw its organisation and undertook comprehensive revisions. OAB endorsed the final version of the protocol manuscript for publication. SS provided vital contributions to the design and structure of the systematic review methodology. Working closely with OAB, he helped draft the protocol and incorporated necessary amendments. SS further contributed insights into potential outcomes and their implications. He ratified the final version of the protocol manuscript for submission. FO spearheaded the development of the search strategy, guiding the selection of databases and criteria for data extraction. He offered expertise on potential statistical analyses and meta-analytical techniques for the study. FO was instrumental in refining the protocol manuscript and approved its submission. SD played an integral role in the data collection, leading initial screenings and data extraction from selected studies. His methodological acumen was essential in assessing study quality and gauging potential biases. SD contributed to refining the protocol manuscript and approved its final submission. OA supervised the entire protocol development process, ensuring strict adherence to systematic review guidelines and providing valuable counsel during challenges. He was pivotal in interpreting potential outcomes and ensuring the protocol’s comprehensiveness. OA critically reviewed and endorsed the protocol manuscript for publication. All authors have meticulously reviewed and endorsed the final version of the protocol manuscript. They collectively vouch for the accuracy and authenticity of the work and commit to addressing any related inquiries comprehensively and transparently.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

References

¹ McDonagh TA, Metra M, Adamo M, et al. 2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J 2021; 42: 3599–726. doi:10.1093/eurheartj/ehab368

² Savarese G, Lund LH. Global public health burden of heart failure. Card Fail Rev 2017; 3: 7–11. doi:10.15420/cfr.2016:25:2

³ Benjamin EJ, Muntner P, Alonso A, et al. Heart disease and stroke Statistics-2019 update: A report from the American heart Association. Circulation 2019; 139: e56–528. doi:10.1161/CIR.0000000000000659

⁴ Bleumink GS, Knetsch AM, Sturkenboom MCJM, et al. Quantifying the heart failure epidemic: prevalence, incidence rate, lifetime risk and prognosis of heart failure the Rotterdam study. Eur Heart J 2004; 25: 1614–9. doi:10.1016/j.ehj.2004.06.038

⁵ Kelaiditi E, Cesari M, Canevelli M, et al. Cognitive frailty: rational and definition from an (I.A.N.A./I.A.G.G.) International consensus group. J Nutr Health Aging 2013; 17: 726–34. doi:10.1007/s12603-013-0367-2

⁶ Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56: M146–56. doi:10.1093/gerona/56.3.m146

⁷ Petersen RC, Caracciolo B, Brayne C, et al. Mild cognitive impairment: a concept in evolution. J Intern Med 2014; 275: 214–28. doi:10.1111/joim.12190

⁸ Almeida OP, Beer C, Lautenschlager NT, et al. Two-year course of cognitive function and mood in adults with congestive heart failure and coronary artery disease: the heart-mind study. Int Psychogeriatr 2012; 24: 38–47. doi:10.1017/S1041610211001657

⁹ Gruhn N, Larsen FS, Boesgaard S, et al. Cerebral blood flow in patients with chronic heart failure before and after heart transplantation. Stroke 2001; 32: 2530–3. doi:10.1161/hs1101.098360

¹⁰ Donal E, Lund LH, Oger E, et al. Value of exercise echocardiography in heart failure with preserved ejection fraction: a Substudy from the Karen study. Eur Heart J Cardiovasc Imaging 2016; 17: jev144. doi:10.1093/ehjci/jev144

¹¹ Rusanen M, Kivipelto M, Levälahti E, et al. Heart diseases and long-term risk of dementia and Alzheimer’s disease: a population-based CAIDE study. J Alzheimers Dis 2014; 42: 183–91. doi:10.3233/JAD-132363

¹² Hjelm C, Dahl A, Broström A, et al. The influence of heart failure on longitudinal changes in cognition among individuals 80 years of age and older. J Clin Nurs 2012; 21: 994–1003.: 8. doi:10.1111/j.1365-2702.2011.03817.x

¹³ Cannon JA, McMurray JJ, Quinn TJ. Hearts and minds: Association, causation and implication of cognitive impairment in heart failure. Alzheimers Res Ther 2015; 7: 22. doi:10.1186/s13195-015-0106-5

¹⁴ Woo J, Yu R, Wong M, et al. Frailty screening in the community using the FRAIL scale. J Am Med Dir Assoc 2015; 16: 412–9. doi:10.1016/j.jamda.2015.01.087

¹⁵ Panza F, Solfrizzi V, Barulli MR, et al. Cognitive frailty: A systematic review of Epidemiological and Neurobiological evidence of an age-related clinical condition. Rejuvenation Res 2015; 18: 389–412. doi:10.1089/rej.2014.1637